Charles R Harris schrieb:
Nope, vdot doesn't work for row and column vectors. So there is *no* builtin inner product that works for matrices. I wonder if we should have one, and if so, what it should be called. I think that vdot should probably be modified to do the job. There is also the question of whether or not v.T * v should be a scalar when v is a column vector. I believe that construction is commonly used in matrix algebra as an alias for the inner product, although strictly speaking it uses the mapping between a vector space and its dual that the inner product provides.
As a matrix-using user and w/o too much thinking, I would suggest to treat inner() as a reduce-like method returning a scalar (I believe such in the context of other functions a similar issue was discussed here some time ago), and leave '*'-style multiplication alone (no special casing there -- actually due to numpy's broadcasting capabilities, it shouldn't be a problem to get a 1,1-matrix in place of a scalar, right?). Thanks for caring about matrices, Sven